Extraordinary growth in mobile business and personal telecommunications over the past decade has driven design efforts for more efficient radio-frequency (RF) spectral utilization and higher data throughput. Wireless local area network (WLAN) technology has undergone so many improvements that the Institute for Electrical and Electronic Engineering (IEEE), which maintains the widely used 802.11 standards, commercially known (and referred to herein) as Wi-Fi™, has had to resort to recycling the alphabet for extending their revision tracking convention. As of the filing of the present application, IEEE 802.11ac is in its late draft stages and standardizes highly anticipated improvements, including, but not limited to wider bandwidth, higher data rates and multi-user (MU) multiple-input/multiple-output (MIMO).
Wider bandwidth, however, carries with it additional challenges in receiver implementation. For example, IEEE 802.11ac specifies a 5 GHz bandwidth that encompasses the RF band for, among other things, certain radar systems. When radar signals are present, Wi-Fi transmitters are prohibited from transmitting in the same band and, accordingly, many equipment manufactures implement Dynamic Frequency Selection (DFS) by which, upon detecting a radar signature in channels through which certain devices are communicating, DFS-enabled equipment can be switched to alternative channels. DFS implementations seek to utilize as much bandwidth as possible and thus a great deal of effort has been devoted toward spectral intelligence (SI) techniques that can accurately identify the presence of different types of signals. For example, if true radar emissions can be discriminated from signals that resemble radar, such as by electromagnetic radiation other than radar that occupies the same band, false reporting of the presence of radar can be averted. In the absence of true radar, a network node may be free to use that portion of its bandwidth that would otherwise be excluded by the false reporting. SI is also being used to identify RF interference in the Wi-Fi band so that its impact can be mitigated, such as by selecting an alternative channel on which to communicate. Microwave ovens, cordless phones, RF jammers, motion detectors, neighboring wireless networks, and wireless security cameras are just a few sources of interference that can severely impact performance of a wireless network. Advanced SI techniques can now identify the source of interference and locate the source on a map. Network management processes can report that location to responsible parties and make automatic adjustments to optimize wireless coverage while the interference remains active.
While implementing SI on Wi-Fi equipment offers many advantages, optimizing the radio receiver for both signal analysis and Wi-Fi communications is key in achieving its maximum benefit. For example, automatic gain control (AGC) for optimal Wi-Fi signal processing is not conducive to optimal SI. Current technologies attempt to apply a common AGC mechanism for all signal processing modes, but as the requirements of Wi-Fi become more demanding, such compromise is no longer a viable solution.